scholarly journals Unraveling hierarchical genetic structure in a marine metapopulation: A comparison of three high‐throughput genotyping approaches

2020 ◽  
Vol 29 (12) ◽  
pp. 2189-2203 ◽  
Author(s):  
Cassidy C. D’Aloia ◽  
Jose A. Andrés ◽  
Steven M. Bogdanowicz ◽  
Amy R. McCune ◽  
Richard G. Harrison ◽  
...  
Keyword(s):  
Genetic Structure ◽  
High Throughput ◽  
Marine Metapopulation

scholarly journals Chinese Fir Breeding in the High-Throughput Sequencing Era: Insights from SNPs

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 681 ◽  
Author(s):  
Huiquan Zheng ◽  
Dehuo Hu ◽  
Ruping Wei ◽  
Shu Yan ◽  
Runhui Wang
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Breeding Population ◽  
Population Diversity ◽  
Chinese Fir ◽  
High Density ◽  
Population Structure Analysis ◽  
Snp Panel

Knowledge on population diversity and structure is of fundamental importance for conifer breeding programs. In this study, we concentrated on the development and application of high-density single nucleotide polymorphism (SNP) markers through a high-throughput sequencing technique termed as specific-locus amplified fragment sequencing (SLAF-seq) for the economically important conifer tree species, Chinese fir (Cunninghamia lanceolata). Based on the SLAF-seq, we successfully established a high-density SNP panel consisting of 108,753 genomic SNPs from Chinese fir. This SNP panel facilitated us in gaining insight into the genetic base of the Chinese fir advance breeding population with 221 genotypes for its genetic variation, relationship and diversity, and population structure status. Overall, the present population appears to have considerable genetic variability. Most (94.15%) of the variability was attributed to the genetic differentiation of genotypes, very limited (5.85%) variation occurred on the population (sub-origin set) level. Correspondingly, low FST (0.0285–0.0990) values were seen for the sub-origin sets. When viewing the genetic structure of the population regardless of its sub-origin set feature, the present SNP data opened a new population picture where the advanced Chinese fir breeding population could be divided into four genetic sets, as evidenced by phylogenetic tree and population structure analysis results, albeit some difference in membership of the corresponding set (cluster vs. group). It also suggested that all the genetic sets were admixed clades revealing a complex relationship of the genotypes of this population. With a step wise pruning procedure, we captured a core collection (core 0.650) harboring 143 genotypes that maintains all the allele, diversity, and specific genetic structure of the whole population. This generalist core is valuable for the Chinese fir advanced breeding program and further genetic/genomic studies.

scholarly journals Genetic structure of the American ginseng (Panax quinquefolius L.) in Eastern Canada using reduced-representation high-throughput sequencing

Botany ◽  
2017 ◽  
Vol 95 (4) ◽  
pp. 429-434 ◽  
Author(s):  
Simon Joly ◽  
Annie Archambault ◽  
Stéphanie Pellerin ◽  
Andrée Nault
Keyword(s):  
Genetic Variation ◽  
Genetic Structure ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Natural Populations ◽  
American Ginseng ◽  
Panax Quinquefolius ◽  
Eastern Canada ◽  
Reduced Representation ◽  
Wide Range

The American ginseng (Panax quinquefolius L.) has been used for a wide range of medicinal purposes for more than 300 years, and is at risk in most of its range because of harvesting in natural populations, herbivory, and habitat loss. Its genetic structure is largely unknown in the previously glaciated areas of Eastern Canada, although such information could provide useful information for restoration strategies. We generated and analysed data from a reduced-representation high-throughput sequencing approach with a BAMOVA population model to partition the genetic variation within and among six natural populations of American ginseng in Eastern Canada. We found that an important and significant fraction of the genetic variation was structured among populations ([Formula: see text] = 42%; FST = 34%) at the geographical scale of the study (<250 km). No clear evidence of isolation-by-distance was observed. This important genetic structure observed among American ginseng populations from a region that was covered by ice during the last glaciations is similar to what had been found in previous studies on southern populations or throughout the species range.

scholarly journals High-throughput genotype based population structure analysis of selected buffalo breeds

2018 ◽  
Author(s):  
Prakash B. Thakor ◽  
Ankit T. Hinsu ◽  
Dhruv R. Bhatiya ◽  
Tejas M. Shah ◽  
Nilesh Nayee ◽  
...  
Keyword(s):  
Population Structure ◽  
Genetic Structure ◽  
Structure Analysis ◽  
Milk Production ◽  
High Throughput ◽  
Snp Markers ◽  
High Density ◽  
Sequence Information ◽  
Snp Chip ◽  
Geographical Regions

AbstractThe water buffalo (Bubalus bubalis) has shown enormous milk production potential in many Asian countries. India is considered as the home tract of some of the best buffalo breeds. However, genetic structure of the Indian river buffalo is poorly understood. Hence, for selection and breeding strategies, there is a need to characterize the populations and understand the genetic structure of various buffalo breeds. In this study, we have analysed genetic variability and population structure of seven buffalo breeds from their respective geographical regions using Axiom® Buffalo Genotyping Array having 124,030 Single Nucleotide Polymorphisms (SNPs). Blood samples were obtained from 302 buffaloes comprising Murrah, Nili-Ravi, Mehsana, Jaffarabadi, Banni, Pandharpuri and Surti breeds. Diversity, as measured by expected heterozygosity (He) ranged from 0.364 in the Surti to 0.384 in the Murrah breed. All the breeds showed negligible inbreeding coefficient. Pair-wise FST values revealed the lowest genetic distance between Mehsana and Nili-Ravi (0.0022) while highest between Surti and Pandharpuri (0.030). Principal component analysis and structure analysis unveiled the differentiation of Surti, Pandharpuri and Jaffarabadi in first two PCs, while remaining breeds were grouped together as a separate single cluster. Murrah and Mehsana showed early linkage disequilibrium decay while Surti breed showed late decay, similarly LD based Ne was drastically declined for Murrah and Mehsana since last 100 generations. In LD blocks to QTLs concordance analysis, 14.19 per cent of concordance was observed with 873 (out of 1144) LD blocks overlapped with 8912 (out of 67804) QTLs. Overall, total 4090 markers were identified from all LD blocks for six types of traits. Results of this study indicated that these SNP markers could differentiate phenotypically distinct breeds like Surti,Pandharpuri and Jaffarabadi but not others. So, there is a need to develop SNP chip based on SNP markers identified by sequence information of local breeds.Author SummaryIndian buffaloes, through 13 recognised breeds, contribute about 49% in total milk production and play a vital role in enhancing the economic condition of Indian farmers. High density genotyping these breeds will allow us to study differences at the molecular level. Evolutionary relationship and phenotypes relations with genotype could be tested with high density genotyping. Breed structure analysis helps to take effective breeding policy decision. In the present study, we have used the high-throughput microarray based genotyping technology for SNP markers. These markers were used for breed differentiation using various genetic parameters. Population structure reflected the proportion of breed admixture among studied breeds. We have also tried to dig the markers associated with traits based LD calculation. However, these SNPs couldn’t explain obvious variation up to the expected level, hence, there is need to develop an indigenous SNP chip based on Indian buffalo populations.

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction
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